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Biology subjects

Loo, C. E.

Publications and source records attributed to Loo, C. E..

2 recordsLinked to original sources

Critical assessment of nanopore sequencing for the detection of multiple forms of DNA modifications

While nanopore sequencing is increasingly used for mapping DNA modifications, it is important to recognize associated false-positive calls, as they can mislead biological interpretations. To assist biologists and methods developers, we describe a framework, modFDR, for rigorous evaluation that emphasizes the use of the false discovery rate with rationally designed negative controls capturing both general background and confounding modifications. Our critical assessment across multiple DNA modifications shows that while nanopore sequencing performs reliably for high-abundance modifications--including 5-methylcytosine (5mC) at CpG sites in mammalian cells and 5-hydroxymethylcytosine (5hmC) in mammalian brain cells--it produces a substantial fraction of false-positive detections for low-abundance modifications, such as 5mC at CpH sites, 5hmC, and N6-methyldeoxyadenine (6mA) in most mammalian cell types. Although newer models improve certain aspects, systematic false positives remain, and we further observe elevated false negatives for 5mCpG when benchmarked against orthogonal enzymatic methods. This study highlights the urgent need to incorporate modFDR into future methods development, evaluation, and biological studies, and advocates prioritizing nanopore sequencing for mapping abundant rather than rare modifications in biomedical applications.

genomics↗

Low-input and single-cell methods for Infinium DNA methylation BeadChips

The Infinium BeadChip is the most widely used DNA methylome assay technology for population-scale epigenome profiling. However, the standard workflow requires over 200 ng of input DNA, hindering its application to small cell-number samples, such as primordial germ cells. We developed experimental and analysis workflows to extend this technology to suboptimal input DNA conditions, including ultra-low input down to single cells. DNA preamplification significantly enhanced detection rates to over 50% in five-cell samples and [~]25% in single cells. Enzymatic conversion also substantially improved data quality. Computationally, we developed a method to model the background signals influence on the DNA methylation level readings. The modified detection p-values calculation achieved higher sensitivities for low-input datasets and was validated in over 100,000 public datasets with diverse methylation profiles. We employed the optimized workflow to query the demethylation dynamics in mouse primordial germ cells available at low cell numbers. Our data revealed nuanced chromatin states, sex disparities, and the role of DNA methylation in transposable element regulation during germ cell development. Collectively, we present comprehensive experimental and computational solutions to extend this widely used methylation assay technology to applications with limited DNA.

bioinformatics↗